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Masters in Business Analytics

Curriculum

This 21-month full-time thesis-based M.S. program emphasizes theory, concepts, modeling approaches, modeling and analysis tools in the context of Business Analytics.

The program seeks to achieve the following learning outcomes:

  • Demonstrated understanding of data-driven decision modeling and analysis concepts and frameworks,
  • Knowledge of and hands-on experience with fundamentals of business analytics, management information systems, statistical and prediction models,
  • Ability to transform complex data into valuable insight and resulting value-adding actions,
  • Skills in hands-on data-mining tools and techniques thereby leading to graduates that are competitive in the Analytics job market,
  • Deeper expertise in a selected line of research using real data.

The required number of courses is 8, which is equivalent to 24 SU credits. After completing the 8-course, students will conduct thesis-based research over the Fall and Spring semesters of their second year.

Fall Semester 1  SU Credits
BAN 500 Introduction to Business Analytics 3
BAN 502 Introduction to Decision Making 3
BAN 599 Graduate Seminars Course 0
ENS 505 Methods of Statistical Inference 3
ENS 511 Engineering Optimization 3
Spring Semester 2  
 Elective Course 1 3
 Elective Course 2 3
 Elective Course 3 3
 Elective Course 4 3
Fall Semester 3  
BAN 600 Master Thesis 0
Spring Semester 4  
BAN 600 Master Thesis  
Course Code Course Name
BAN 503 Management Information Systems
BAN 504 Data Mining with SAS Enterprise Miner
BAN 521 / OPIM 523 Decision Models 
BAN 522 Revenue Management
BAN 523 Group Decision Making under Multiple Criteria
BAN 524 / OPIM 506 CRM using Location Intelligence
BAN 526 / OPIM 526 Business Intelligence and Decision Support Systems
BAN 525 / ECON 501 Microeconomics I
BAN 528 / ECON 502 Microeconomics II
BAN 529 / ECON 506 Econometrics
BAN 533 / IE 503 Stochastic Processes
BAN 531 / IE 523 System Simulation
BAN 537 / IE 527 System Dynamics
BAN 535 / CS 515 Neural Networks
BAN 532 / CS 512 Machine Learning
BAN 539 / CS 525 Data Mining

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